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Biodiversity initiative: Integrating Taxonomy , Genomics and Biodiversity. +. +. = ?????. Speaker: Benjamin Linard. Alfried Vogler Team. Arthropods metagenomics. 1 / 8. 1 SAMPLE: 480 beetle specimens captured in Borneo. Mixed sample. All 480 beetles. DNA extraction.
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Biodiversity initiative: IntegratingTaxonomy, Genomics and Biodiversity + + = ????? Speaker: Benjamin Linard AlfriedVogler Team
Arthropods metagenomics 1/ 8 1 SAMPLE: 480 beetle specimens captured in Borneo Mixed sample All 480 beetles DNA extraction PCR barcodes Est. 288 species Pool DNA by volume Mitochondrial contigs De novo assembly into contigs 1x IlluminaMiSeq run (8.5Gb)
Mitochondrial DNA 2/ 8 Results of Alex Crampton Plat Harpalinae Buprestidae Log(Biomass) = -2.37 + 0.85(log(No. Reads)) P<0.001; F1,84=73.32; R2=0.47 ~5% beetle mitochondrial DNA Tenebrionidae Coccinelidae Chrysomelidae Curculionidae
Genomic information ? 3/ 8 Genomic analyses Functional information ? Tribolium castaneum, chromosome 3 TaxomomyAbundance ~5% beetle mitochondria Homologous DNA between 4 beetle metagenomic samples # homologous contigs ~95% genomic information , ~45 % is Coleoptera DNA position Chromosome region with known sequence NNNN region (unresolved sequence) Homologous contig % GC
Arthropods metagenomics 4/ 8 Computational requirementsto analyse 1 arthropod soup : Server: ~128Gb RAM, 24 cores Xeon 2.4 GHz Assemblies ( in the best case... when data complexity is manageable by current algorithms ) Our last DNA assembly Successful Several assemblies (~1.5 per week) Aborted One assembly at a time, unpredictible risk of memory overload
Arthropods metagenomics 5/ 8 Computational requirementsto analyse 1 arthropod soup : Server: ~128Gb RAM, 24 cores Xeon 2.4 GHz Assemblies ( in the best case... when data complexity is manageable by current algorithms ) Genomic analyses : Need support of SQL database. Currenlty ~ 300 Gb
Biodiversity & functional analysis 5/ 8 Future ? for the analysis of 1 arthropod soup • Growth of analysis pipeline ! • More CPU to perform a complete metagenomic analyses • standard MIGS (D Field & al, 2008) • standards MINIMESS (J Raes & al, 2007) ~1 000 arthropods trancriptomes/genomes ~50 beetle species transcriptomes ~50 beetle draft/complete genomes Long term perspective: Disk space consuming... # more reference genomes # larger/more complex databases
Arthropods biodiversity 6/ 7 n traps per site: (soil, canopy, Ground…) N plots Many soup analyses... • Mitochondrial analysis, not a problem • Full DNA analysis... • Which computational power could we access ? • More computations to answer more interesting questions • Pooling DNA? We will loose metagenomic resolution... • More complex assemblies
A source of DNA collection 7/ 8 Metadata(1 arthropod soup) General: Sampling localisation, date, methods... Mitochondrial information: Identified species/taxons Abundance Other identified species (plants, fungi...) Genomic information: Identified genes Identified functions (sugar degradation) Soup metadata 24 unidentified tenebrionidae from Madagascar access Soup metadata 125 species, French Guyana NHM data portal Kemu Integration, links, queries ... Scientific community Soup metadata 24 species, Congo, Soup metadata 53 species + abundance data in NHM 8 specimens, 4 images, 2 metagenomic samples ... “I want all NHM collection data concerning the species X” Data storage ? NHM databases integration ?
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